【摘要】 将人工免疫系统运用到入侵检测系统中,近年来已经有了一定的发展。在这个领域中,如何培育出符合需求的免疫细胞,使能够较多地识别非我并较少地识别自我,尽可能地覆盖NONSELF空间,这就是如何培育更好的识别器的问题。反向选择算法是识别器的传统构造算法,该文针对反向选择算法的伪肯定率过高的问题,提出了改进算法,在入侵检测系统中达到的效果更好。更多还原

【Abstract】 Immunity experts developed intrusion detection system by using artificial immune system these years.In this field,how to use the principles of artificial immune system to train the detectors and make the detectors distinguishing nonself from self well and covering with the space of nonself.It is an important issue to train the detectors.The negative selection algorithm advanced by forrest is the basic algorithm for training the detectors.The algorithms this paper proposed describe the space of nonself well and depress the NSA’s false affirmation rate.The effect for the IDS is better.更多还原